The increasing availability of biomedical data from large biobanks, electronic health records,
medical imaging, wearable and ambient biosensors, and the lower cost of genome and …

The recent developments in Triboelectric Nanogenerator (TENG) devices, which gather
biomechanical energy from the human body movement, have been outstanding. The output …

Recent substantial advancements in computational techniques, particularly in artificial
intelligence (AI) and machine learning (ML), have raised the demand for smart self-powered …

Background Improved breast cancer risk assessment models are needed to enable
personalized screening strategies that achieve better harm-to-benefit ratio based on earlier …

This study examines the ethical issues surrounding the use of Artificial Intelligence (AI) in
healthcare, specifically nursing, under the European General Data Protection Regulation …

Accelerated by telemedicine, advances in Remote Photoplethysmography (rPPG) are
beginning to offer a viable path toward non-contact physiological measurement …

The application of artificial intelligence and machine learning (ML) technologies in
healthcare have immense potential to improve the care of patients. While there are some …

Training on multiple diverse data sources is critical to ensure unbiased and generalizable
AI. In healthcare, data privacy laws prohibit data from being moved outside the country of …

Artificial intelligence (AI) offers much promise for improving healthcare. However, it runs the
looming risk of causing individual and societal harms; for instance, exacerbating inequalities …

Abstract Artificial Intelligence (AI) and Machine Learning (ML) are powerful tools shaping the
healthcare sector. This review considers twelve key aspects of AI in clinical practice: 1) …